Electronic and Cyber Defense

Electronic and Cyber Defense

Energy Efficiency in Smart Vehicular Networks Using Dynamic Load Migration

Document Type : Original Article

Authors
zahra Sharifi 1
abbas horri 2
leila samimi 2
1 Master's degree, Shahrekord University, Shahrekord, Iran
2 Assistant Professor, Shahrekord University, Shahrekord, Iran
10.47176/ECDJ.2025.1632
Abstract
Modern smart vehicles are connected to complex communication networks and exchange a massive volume of data, leading to increased energy consumption in these networks. In this study, a novel method for optimizing energy consumption in smart vehicular networks is proposed. The proposed approach is based on two dynamic load balancing techniques: First, determine dynamic thresholds based on the average workload of virtual machines, then, predict future load using regression analysis. Simulation results demonstrate that using 10% and 20% higher than the average workload threshold reduces energy consumption and improves load balancing efficiency. Additionally, the workload prediction model shows only a 5% deviation between predicted and actual values, indicating high accuracy. This algorithm significantly reduces energy consumption and improves the success rate of virtual machine migrations. The proposed method can be further utilized for efficient resource management in smart vehicular networks, contributing to lower operational costs and environmental sustainability
Keywords
Smart vehicle
Internet of Things (IoT)
Dynamic load migration
Energy consumption optimization
Vehicular networks
Subjects
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Electronic and Cyber Defense
Volume 13, Issue 4 - Serial Number 52
Winter
Winter 2026
Pages 77-88

  • Receive Date 08 October 2025
  • Revise Date 02 December 2025
  • Accept Date 15 December 2025
  • Publish Date 22 December 2025